Solar Blue Light Radiation Enhancement during Mid to Low Solar Elevation Periods under Cloud Affected Skies.

Solar blue-violet wavelengths (380-455 nm) are at the high energy end of the visible spectrum; referred to as "high energy visible" (HEV). Both chronic and acute exposure to these wavelengths has been often highlighted as a cause for concern with respect to ocular health. The sun is the source of HEV which reaches the Earth's surface either directly or after scattering by the atmosphere and clouds. This research has investigated the effect of clouds on HEV for low solar elevation (solar zenith angles between 60° and 80°), simulating time periods when the opportunity for ocular exposure in global populations with office jobs is high during the early morning and late afternoon. The enhancement of "bluing" of the sky due to the influence of clouds was found to increase significantly with the amount of cloud. A method is presented for calculating HEV irradiance at sub-tropical latitudes from the more commonly measured global solar radiation (300-3000 nm) for all cases when clouds do and do not obscure the sun. The method; when applied to global solar radiation data correlates well with measured HEV within the solar zenith angle range 60° and 80° (R2 = 0.82; mean bias error (MBE) = -1.62%, mean absolute bias error (MABE) = 10.3% and root mean square error (RMSE) = 14.6%). The technique can be used to develop repeatable HEV hazard evaluations for human ocular health applications.

The geospatial relationship of pterygium and senile cataract with ambient solar ultraviolet in tropical Ecuador.

Tropical Ecuador presents a unique climate in which we study the relationship between the ambient levels of solar ultraviolet radiation and eye disease in the absence of a latitudinal gradient. The national distribution of surface ultraviolet, taking into account MODIS and OMI satellite observation of aerosol, ozone, surface albedo, local elevation and cloud fractions measured during 2011, was compared with the national pterygium (WHO ICD H11) and senile cataract (WHO ICD H25) incidence projected from the 2010 National Institute of Statistics and Census (Ecuador). Public Health Ministry projections for age categories 0 to 39, 40 to 59 and 60+ years were compared to surface ultraviolet irradiance data in 1040 parishes. Correlations drawn between modelled surface ultraviolet and eye disease incidence show a significant increase in both pterygium and senile cataract in the highest ambient exposure regions of the Pacific coast and western lowlands with incidence rates of 34.39 and 16.17 per 100 000 residents respectively. The lowest rates of incidence for pterygium (6.89 per 100 000) and senile cataract (2.90 per 100 000) were determined in high altitude sites and are attributed here to increased daily cloud fraction for parishes located in the Andean mountain range. The South American Andes experience the highest solar UV exposures on Earth and report frequent high incidence of keratinocyte cancer. Our results show the high Andes to be the location of the lowest eye disease incidence suggesting that both pterygium and senile cataract are the result of cumulative exposure to solar ultraviolet. These findings have clear implications for the agricultural workers and fishermen of the lowland districts of Ecuador, contrary to conventional understanding that greater risks are faced in locations of high altitude.

Smartphone Spectrometers.

Smartphones are playing an increasing role in the sciences, owing to the ubiquitous proliferation of these devices, their relatively low cost, increasing processing power and their suitability for integrated data acquisition and processing in a 'lab in a phone' capacity. There is furthermore the potential to deploy these units as nodes within Internet of Things architectures, enabling massive networked data capture. Hitherto, considerable attention has been focused on imaging applications of these devices. However, within just the last few years, another possibility has emerged: to use smartphones as a means of capturing spectra, mostly by coupling various classes of fore-optics to these units with data capture achieved using the smartphone camera. These highly novel approaches have the potential to become widely adopted across a broad range of scientific e.g., biomedical, chemical and agricultural application areas. In this review, we detail the exciting recent development of smartphone spectrometer hardware, in addition to covering applications to which these units have been deployed, hitherto. The paper also points forward to the potentially highly influential impacts that such units could have on the sciences in the coming decades.

Very short-term reactive forecasting of the solar ultraviolet index using an extreme learning machine integrated with the solar zenith angle.

Exposure to erythemally-effective solar ultraviolet radiation (UVR) that contributes to malignant keratinocyte cancers and associated health-risk is best mitigated through innovative decision-support systems, with global solar UV index (UVI) forecast necessary to inform real-time sun-protection behaviour recommendations. It follows that the UVI forecasting models are useful tools for such decision-making. In this study, a model for computationally-efficient data-driven forecasting of diffuse and global very short-term reactive (VSTR) (10-min lead-time) UVI, enhanced by drawing on the solar zenith angle (θs) data, was developed using an extreme learning machine (ELM) algorithm. An ELM algorithm typically serves to address complex and ill-defined forecasting problems. UV spectroradiometer situated in Toowoomba, Australia measured daily cycles (0500-1700h) of UVI over the austral summer period. After trialling activations functions based on sine, hard limit, logarithmic and tangent sigmoid and triangular and radial basis networks for best results, an optimal ELM architecture utilising logarithmic sigmoid equation in hidden layer, with lagged combinations of θs as the predictor data was developed. ELM's performance was evaluated using statistical metrics: correlation coefficient (r), Willmott's Index (WI), Nash-Sutcliffe efficiency coefficient (ENS), root mean square error (RMSE), and mean absolute error (MAE) between observed and forecasted UVI. Using these metrics, the ELM model's performance was compared to that of existing methods: multivariate adaptive regression spline (MARS), M5 Model Tree, and a semi-empirical (Pro6UV) clear sky model. Based on RMSE and MAE values, the ELM model (0.255, 0.346, respectively) outperformed the MARS (0.310, 0.438) and M5 Model Tree (0.346, 0.466) models. Concurring with these metrics, the Willmott's Index for the ELM, MARS and M5 Model Tree models were 0.966, 0.942 and 0.934, respectively. About 57% of the ELM model's absolute errors were small in magnitude (±0.25), whereas the MARS and M5 Model Tree models generated 53% and 48% of such errors, respectively, indicating the latter models' errors to be distributed in larger magnitude error range. In terms of peak global UVI forecasting, with half the level of error, the ELM model outperformed MARS and M5 Model Tree. A comparison of the magnitude of hourly-cumulated errors of 10-min lead time forecasts for diffuse and global UVI highlighted ELM model's greater accuracy compared to MARS, M5 Model Tree or Pro6UV models. This confirmed the versatility of an ELM model drawing on θsdata for VSTR forecasting of UVI at near real-time horizon. When applied to the goal of enhancing expert systems, ELM-based accurate forecasts capable of reacting quickly to measured conditions can enhance real-time exposure advice for the public, mitigating the potential for solar UV-exposure-related disease.

Investigation on the capability of polysulphone for measuring biologically effective solar UV exposures.

Polysulphone (PS) dosimetry is a well-known technique broadly used to assess the erythemally effective solar UV dose received by anatomical sites (personal exposure). We investigate the capability of PS dosimetry to convert doses absorbed by PS badges into biologically effective solar UV exposures taking as examples two relevant effects for human skin: erythema induction and pre-vitamin D3 production. PS calibration curves for erythemal and pre-vitamin D3 were distinctly determined by using an empirical relationship between the biologically effective UV exposures and the PS absorbance change. This relationship is parameterized by a coefficient, distinct for each of the two considered biological effects, multiplying the same cubic polynomial function. It is shown how the multiplying coefficient is related to the ratio between the biologically effective and the PS weighted irradiances which is the prevailing factor affecting the accuracy of the calibration and, consequently, the capability of PS films for measuring biologically effective solar UV exposures. The points addressed in this paper can be extended to other biological effects of interest whose action spectra have some similarity with the PS film response.

The mitigating effect of street trees, urban flora, and the suburban environment on seasonal peak UV indices: A case study from Brisbane, Australia.

Tree shade, particularly shade that obscures direct sunlight near peak periods of midday solar exposure can have a pronounced effect on potentially harmful ultraviolet radiation, and in turn, strongly influence the maximum daily UV index (UVI). In this study, the seasonal influence of tree shade on the UVI is evaluated from 210 hemispherical sky view images collected alongside public walkways and footpaths from 10 residential Brisbane suburbs. The effective sidewalk UV index is calculated underneath planted tree canopies, adjacent residential gardens, buildings and background tree species. Results are presented with respect to seasonal variations in the diurnal solar elevation for each month of the year at Brisbane's latitude. The research also examines the total reduction in UVI due to the presence of individual tree species, showing reductions in the midday UVI of up to 91% of an equivalent unimpeded sky hemisphere when overhead tree canopies are present. Important footpath tree species for peak midday UVI mitigation include Pongamia pinnata, Xanthostemon chrysanthus, Senna siamea, and Libidibia ferrea. The planting and maintenance of existing tree species already growing alongside residential Brisbane streets will improve the shade characteristics of suburbs and enhance UV protection for local residents.

Influence of reflected UV irradiance on occupational exposure from combinations of reflective wall surfaces.

Outdoor workers who occupationally spend large periods of time exposed to ultraviolet irradiance are at increased risk of developing certain types of non-melanoma skin cancer in addition to being prone to erythema and eye damage. UV exposure to workers is affected by a number of factors including geographic location, season, individual biological factors and the local surroundings. Urban environments can provide surrounds that contain surfaces that reflect UV radiation which can enhance UV exposure to construction workers, in both the vertical as well as horizontal plane. However it was unknown how different constructed configurations of the surfaces may additionally influence UV exposure for a worker, such as corners opposed to walls. This study shows that for highly UV reflective surfaces the influence on erythemal UV exposure is approximately the same regardless of constructive type, but there is statistically significant difference observed for lower UV reflecting surfaces in conjunction with constructive type. This is comparable to influence of body site on relative UV exposure, and together may provide a method that may assist in reduction in UV exposures. Regression analysis provides a more effective means to determine a UV reflective factor for a surface type, than previously used averaging methods. Additionally, this knowledge may be used by workers, workplaces and advisory bodies to assist with developing further protective strategies that aim to provide more moderate UV exposures to outdoor workers.

Enhanced joint hybrid deep neural network explainable artificial intelligence model for 1-hr ahead solar ultraviolet index prediction.

BACKGROUND AND OBJECTIVE: Exposure to solar ultraviolet (UV) radiation can cause malignant keratinocyte cancer and eye disease. Developing a user-friendly, portable, real-time solar UV alert system especially or wearable electronic mobile devices can help reduce the exposure to UV as a key measure for personal and occupational management of the UV risks. This research aims to design artificial intelligence-inspired early warning tool tailored for short-term forecasting of UV index (UVI) integrating satellite-derived and ground-based predictors for Australian hotspots receiving high UV exposures. The study further improves the trustworthiness of the newly designed tool using an explainable artificial intelligence approach. METHODS: An enhanced joint hybrid explainable deep neural network model (called EJH-X-DNN) is constructed involving two phases of feature selection and hyperparameter tuning using Bayesian optimization. A comprehensive assessment of EJH-X- DNN is conducted with six other competing benchmarked models. The proposed model is explained locally and globally using robust model-agnostic explainable artificial intelligence frameworks such as Local Interpretable Model-Agnostic Explanations (LIME), Shapley additive explanations (SHAP), and permutation feature importance (PFI). RESULTS: The newly proposed model outperformed all benchmarked models for forecasting hourly horizons UVI, with correlation coefficients of 0.900, 0.960, 0.897, and 0.913, respectively, for Darwin, Alice Springs, Townsville, and Emerald hotspots. According to the combined local and global explainable model outcomes, the site-based results indicate that antecedent lagged memory of UVI and solar zenith angle are influential features. Predictions made by EJH-X-DNN model are strongly influenced by factors such as ozone effect, cloud conditions, and precipitation. CONCLUSION: With its superiority and skillful interpretation, the UVI prediction system reaffirms its benefits for providing real-time UV alerts to mitigate risks of skin and eye health complications, reducing healthcare costs and contributing to outdoor exposure policy.

Serial Cross-Sectional Observations of Sun-Protective Behaviors at an Annual Outdoor Motorsport Event in Tropical Queensland, Australia.

Skin cancer, the most prevalent cancer in Caucasians residing at low latitudes, can primarily be prevented by avoiding overexposure to sunlight. Serial cross-sectional observations were conducted at an outdoor motorsport event held in Townsville, Queensland each July (Southern winter) to determine whether sun-protection habits changed over time. Most (71.1%) of the 1337 attendees observed (97.6% lightly pigmented skin, 64.0% male) wore a hat (any style shading the face), while few (18.5%) wore three-quarter or full-length sleeves. While hat-wearing rates (any style) were similar in 2009 (326, 72.6%) and 2013 (625, 70.4%), the use of sun-protective styles (wide-brimmed/bucket/legionnaires) decreased from 29.2% to 18.6% over the same period, primarily because the use of sun-protective hats halved (from 28.7% to 14.0%) among females, while decreasing from 29.4% to 21.1% in males. Although relatively few individuals wore sun-protective (three-quarter-length or full-length) sleeves regardless of year (OR = 0.117, P < 0.0001), encouragingly, the use of sun-protective sleeves more than doubled between 2009 (10.5%) and 2013 (22.5%). Interestingly females, albeit the minority, at this sporting event were less likely to wear a hat (OR = 0.473, P < 0.0001) than males. These findings highlight the need for continued momentum toward skin cancer primary prevention through sun protection with a dedicated focus on outdoor sporting settings.

The Playground Shade Index: A New Design Metric for Measuring Shade and Seasonal Ultraviolet Protection Characteristics of Parks and Playgrounds.

Current shading strategies used to protect outdoor playgrounds from harmful solar radiation include the placement of artificial cloth weaves or permanent roofing over a playground site, planting trees in proximity to playground equipment, and using vegetation or surface texture variations to cool playground surfaces. How and where an artificial shade structure is placed or a tree is planted to maximize the shade protection over specific playground areas, requires careful assessment of local seasonal sun exposure patterns. The Playground Shade Index (PSI) is introduced here as a design metric to enable shade and solar ultraviolet exposure patterns to be derived in an outdoor space using conventional aerial views of suburban park maps. The implementation of the PSI is demonstrated by incorporating a machine learning design tool to classify the position of trees from an aerial image, thus enabling the mapping of seasonal shade and ultraviolet exposure patterns within an existing 7180 m2 parkland. This is achieved by modeling the relative position of the sun with respect to nearby buildings, shade structures, and the identified evergreen and deciduous tree species surrounding an outdoor playground.

Influence of high levels of cloud cover on vitamin D effective and erythemal solar UV irradiances.

The solar irradiances for the initiation of vitamin D synthesis (UV(D3)) have been measured concurrently with the amount of cloud cover to investigate the influence of high cloud cover fraction. The cases of 6.5 and more octa cloud cover were considered for five solar zenith angle (SZA) ranges up to 80°. For each of the SZA ranges, the UV(D3) reduced due to the high cloud cover. The average of the ratios of the UV(D3) irradiances on a cloudy day to those on a clear day with the corresponding ozone and SZA are 0.71 for the 6.5-7.5 octa cloud and 0.45 for the more than 7.5 octa cloud ranges. The exposure times necessary to receive 1/3 MED to a horizontal plane were found to increase as the amount of cloud cover increased. For each cloud cover category, the range of values increased with cloud cover and with SZA. This research shows that the current public recommendations on the times of solar UV exposures required to produce adequate vitamin D are inappropriate for situations of more than 6.5 octa cloud.

A Case Study of UV Exposure Risk in Sydney during the 2019/2020 New South Wales Bushfires.

During summer of 2019/2020, Sydney, Australia, experienced several days of extreme air pollution and low visibility due to bushfires. This research presents a case study that investigates the erythemal UV irradiance and resulting 1 h erythemal and 8 h actinic exposures during the worst of these days. Air quality, meteorological and UV data used in the analysis were readily available online or by request from governmental agencies. Analysis showed that even for the lowest visibility day (which had a minimum visibility of less than a kilometer) on 10 December 2019, there was a cumulative 1 h erythemal UV exposure of over 4 SED (standard erythema dose) and a cumulative 8 h exposure of 17 SED by the late afternoon. The 1 h exposure exceeded that of a minimum erythemal dose. Even on this extremely hazy day, these cumulative exposures are enough to exceed the recommended daily exposure limit for actinic exposures weighted with the health sensitivity spectrum for the skin and eyes set by the International Commission of Non-Ionizing Radiation Protection.

Evaluation of the Long-term Cumulative UVA Facial Exposure of Queensland School Teachers derived for an Extended Period from the OMI Satellite Irradiance.

This research presents a novel methodology for deriving the total daily broadband solar UVA (320-400 nm) received by school teachers during their working day from Ozone Monitoring Instrument (OMI) satellite solar noon UVA irradiance measurements for a Queensland subtropical site (27.5°S, 152°E). Daily UVA exposures are weighted to the anatomical human cheek (anterior infra-orbital region) for teachers wearing and not wearing broad-brimmed hats. The method utilizes the OMI UVA irradiance data collected daily at high temporal resolution over 2005 to 2016 to derive the total daily UVA exposure to a horizontal plane. These horizontal plane exposures are scaled by factors to take into account the timing of outdoor activity. The relationship between exposures to a horizontal plane and those to a vertical plane and the protection provided by a broad-brimmed hat was assessed to evaluate the total daily UVA exposures to the cheek for classroom and physical education teaching staff expected to be outside at different periods of the day. The developed method enables the total daily UVA exposure to specific anatomical sites to be evaluated from the satellite solar noon irradiance at locations that do not have access to surface-based instrumentation capable of recording in the solar UVA waveband.

Electronic Sun Journal Versus Self-report Sun Diary: A Comparison of Recording Personal Sunlight Exposure Methods.

This research compared personal sunlight exposure times monitored electronically within suburban Australian environments against self-report paper journals for determining the timing and total duration of individual exposure to daily solar radiation. A total of 90 Electronic Sun Journal (ESJ) daily readings and self-report timing and duration estimates of exposure for weekend and weekdays were compared. A Wilcoxon ranked sign test showed a significant difference (V = 157, P < 0.001) between the duration of exposure recorded electronically and the duration of exposure that was self-reported in a diary. There was also found to be a statistically significant difference between total exposure time measured using both methods for weekends (V = 10, P < 0.001) and weekdays (V = 87, P < 0.001). General trends in outdoor exposure timing confirmed that the most frequent daily exposures received over the weekend occurred between 1 and 2 h earlier than the most frequent exposures received on weekdays. This preliminary research found that exposure durations as recorded by the ESJ were longer on the weekends compared to weekdays (W = 402, P < 0.001) and confirmed that the ESJ is a viable alternative to self-reporting diaries.

Phenothiazine UVA dosimeter: characteristics and performance.

This paper provides an overview of the characteristics of a phenothiazine-mylar dosimeter which can be used as an effective solar UVA exposure assessment tool. This dosimeter is sensitive to UVA wavelengths (315-400 nm); its performance has been characterized in a series of tests such as (a) UVA exposure response (dose-response), (b) temperature stability of the response, (c) impact of long term storage, and (d) angular response. There is no effect of long term storage post-exposure and no effect of temperature up to 30 degrees C. For angles up to 70 degrees, the cosine error of the normalized UVA is less than approximately 0.1. These characterizations have confirmed the reliability and reproducibility of a phenothiazine-mylar combined dosimeter as an effective solar UVA exposure tool for field-based studies of the UVA exposures to population groups.

A hybrid air quality early-warning framework: An hourly forecasting model with online sequential extreme learning machines and empirical mode decomposition algorithms.

Modelling air quality with a practical tool that produces real-time forecasts to mitigate risk to public health continues to face significant challenges considering the chaotic, non-linear and high dimensional nature of air quality predictor variables. The novelty of this research is to propose a hybrid early-warning artificial intelligence (AI) framework that can emulate hourly air quality variables (i.e., Particulate Matter 2.5, PM2.5; Particulate Matter 10, PM10 and lower atmospheric visibility, VIS), the atmospheric variables associated with increased respiratory induced mortality and recurrent health-care cost. Firstly, hourly air quality data series (January-2015 to December-2017) are demarcated into their respective intrinsic mode functions (IMFs) and a residual sub-series that reveal patterns and resolve data complexity characteristics, followed by partial autocorrelation function applied to each IMF and residual sub-series to unveil historical changes in air quality. To design the prescribed hybrid model, the data is partitioned into training (70%), validation (15%) and testing (15%) sub-sets. The online sequential-extreme learning machine (OS-ELM) algorithm integrated with improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is designed as a data pre-processing system to robustly extract predictive patterns and fine-tune the model generalization to a near-optimal global solution, which represents modelled air quality at hourly forecast horizons. The resulting early warning AI-based framework denoted as ICEEMDAN-OS-ELM model, is individually constructed by forecasting each IMF and residual sub-series, with hourly PM2.5, PM10, and VIS obtained by the aggregated sum of forecasted IMFs and residual sub-series. The results are benchmarked with many competing predictive approaches; e.g., hybrid ICEEMDAN-multiple-linear regression (MLR), ICEEMDAN-M5 model tree and standalone versions: OS-ELM, MLR, M5 model tree. Statistical metrics including the root-mean-square error (RMSE), mean absolute error (MAE), Willmott's Index (WI), Legates & McCabe's Index (ELM) and Nash-Sutcliffe coefficients (ENS) are used to evaluate the model's accuracy. Both visual and statistical results show that the proposed ICEEMDAN-OS-ELM model registers superior results, outperforming alternative comparison approaches. For instance, for PM2.5,ELM values ranged from 0.65-0.82 vs. 0.59-0.77 for ICEEMDAN-M5 tree, 0.59-0.74 for ICEEMDAN-MLR, 0.28-0.54 for OS-ELM, 0.27-0.54 for M5 tree and 0.25-0.53 for the MLR model. For remaining air quality variables (i.e., PM10 & VIS), the objective model (ICEEMDAN-OS-ELM) outperformed the comparative models. In particular, ICEEMDAN-OS-ELM registered relatively low RMSE/MAE, ranging from approximately 0.7-1.03 µg/m3(MAE), 1.01-1.47 µg/m3(RMSE) for PM2.5 whereas for PM10, these metrics registered a value of 1.29-3.84 µg/m3(MAE), 3.01-7.04 µg/m3(RMSE) and for Visibility, they were 0.01-3.72 µg/m3 (MAE (Mm-1)), 0.04-5.98 µg/m3 (RMSE (Mm-1)). Visual analysis of forecasted and observed air quality through a Taylor diagram illustrates the objective model's preciseness, confirming the versatility of early warning AI-model in generating air quality forecasts. The excellent performance ascertains the hybrid model's potential utility for air quality monitoring and subsequent public health risk mitigation.

A review on the ability of smartphones to detect ultraviolet (UV) radiation and their potential to be used in UV research and for public education purposes.

The effects of ultraviolet (UV) radiation on life on Earth have continuously been the subject of research. Over-exposure to UV radiation is harmful, but small amounts of exposure are required for good health. It is, therefore, crucial for humans to optimise their own UV exposure and not exceed UV levels that are sufficient for essential biological functions. Exceeding those levels may increase risk of developing health problems including skin cancer and cataracts. Smartphones have been previously investigated for their ability to detect UV radiation with or without additional devices that monitor personal UV exposure, in order to maintain safe exposure times by individuals. This review presents a comprehensive overview of the current state of smartphones' use in UV radiation monitoring and prediction. There are four main methods for UV radiation detection or prediction involving the use smartphones, depending on the requirements of the user: devoted software applications developed for smartphones to predict UV Index (UVI), wearable and non-wearable devices that can be used with smartphones to provide real-time UVI, and the use of smartphone image sensors to detect UV radiation. The latter method has been a growing area of research over the last decade. Built-in smartphone image sensors have been investigated for UV radiation detection and the quantification of related atmospheric factors (including aerosols, ozone, clouds and volcanic plumes). The overall practicalities, limitations and challenges are reviewed, specifically in regard to public education. The ubiquitous nature of smartphones can provide an interactive tool when considering public education on the effects and individual monitoring of UV radiation exposure, although social and geographic areas with low socio-economic factors could challenge the usefulness of smartphones. Overall, the review shows that smartphones provide multiple opportunities in different forms to educate users on personal health with respect to UV radiation.

Biologically effective solar ultraviolet exposures and the potential skin cancer risk for individual gold medalists of the 2020 Tokyo Summer Olympic Games.

Personal solar ultraviolet radiation exposure models were developed for 144 Olympic events scheduled outdoors from across the 33 sport disciplines that will compete in Tokyo between 24 July and 9 August 2020. Ambient exposure models were developed from existing atmospheric parameters measured over Tokyo (35.7°N 139.7°E) and were used to weight erythemally effective solar ultraviolet exposure to gold medalists, taking into account body posture and expected protection by competitor's clothing which was assessed in comparison to respective medalists of the 2016 Rio Olympics. Individual exposure models consider the ultraviolet surface albedo (lawn, concrete, water or sand) and timing of daily events held within Olympic venues. Exposure assessments are presented, including assessments of all preliminary rounds and qualifiers. Within scheduled outdoor events, we award first place (representing the highest and most harmful UV exposure) to the women's tennis singles (1680 J/m2), second to men's golf (1530 J/m2) and third to the men's cycling road race (941 J/m2) for the highest expected erythemally effective solar ultraviolet radiation exposures of the 2020 Tokyo Games. The highest expected solar ultraviolet exposures for nations expected to win greater than three gold medals among the outdoor events were found to occur in athletes from Kenya followed closely by the United States and Hungary. Gold medalists from South Korea were found to demonstrate the highest level of sun protection due to clothing at the 2016 Rio Games, and are thus expected to receive the greatest relative reduction in erythemally effective exposure during the 2020 Tokyo Games.

Comparison of GOME-2 UVA Satellite Data to Ground-Based UVA Measurements in South Africa.

Satellite estimates of surface ultraviolet A (UVA) (315-400 nm) from the Global Ozone Monitoring Experiment (GOME)-2 were compared to ground-based measurements at four stations in South Africa for 2015. The comparison of daily exposure and daily maximum irradiance was completed for all-sky and clear-sky conditions. There is a strong linear correlation between the satellite and ground-based data with a correlation coefficient (r) between 0.86 and 0.97 for all-sky conditions. However, at three of the stations the satellite data are underestimated compared to ground-based data with a mean bias error (MBE) between -8.7% and -20.6%. A seasonal analysis indicated that there is a link between the bias in ground-based and GOME-2 UVA and cloud fraction. Factors such as aerosols, surface albedo, altitude and data resolution may contribute to the underestimations found at the three sites. These results indicate that satellite estimates of surface UVA over South Africa do not exhibit the same behavior as other stations around the world and therefore require further validation.

The Simulated Ocular and Whole-Body Distribution of Natural Sunlight to Kiteboarders: A High-Risk Case of UVR Exposure for Athletes Utilizing Water Surfaces in Sport.

Kiteboarding is an aquatic sporting discipline that has not yet been considered in the literature to date in terms of solar ultraviolet radiation (UVR) measurement. Kiteboarders need to look upward and are placed obliquely relative to the horizon when towed behind an overhead kite over a reflective water surface. This research defines the typical body surface orientation of a kiteboarder in motion through video vector analysis and demonstrates the potential risk to ocular and skin surface damage through practical measurement of solar UVR using a manikin model. Video analysis of 51 kiteboarders was made to construct skeletal wireframes showing the surface orientation of the leg, thigh, spine, humerus, lower arm and head of a typical kiteboarder. Solar UVR dosimeter measurements made using a manikin model demonstrate that the vertex and anterior surfaces of the knee, lower leg and lower humerus received 89%, 90%, 80% and 63% of the available ambient UVR, respectively, for a typical kiteboarder who is tilted back more than 15° from vertical while in motion. Ocular (periorbital) exposures ranged from 56% to 68% of ambient. These new findings show that the anterior skin surfaces of kiteboarders and the eye are at elevated risk of solar UVR damage.